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510(k) Data Aggregation
(351 days)
The DEFEND Ear-Loop Face Masks are intended to be worn to protect both the patient and healthcare professional from transfer of microorganisms, body fluids, and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device, provided non-sterile.
The DEFEND Ear-Loop Face Masks are comprised of four layers of nonwoven materials ultrasonically welded together along the edges with ear loops ultrasonically welded to the sides. The four layers include an outer layer (faces outward when worn), filtration layer, middle layer, and inner layer (faces the user). The materials used in this mask meet the performance requirements for Level 3 stated in ASTM F2100 -19 Performance of Materials Used in Medical Face Masks. The mask is secured to the face with ear loops. The mask also includes a form-fitting pliable nose piece to improve fit and reduce gaps for maximum protection.
The provided document describes the K201127 submission for DEFEND Ear-loop Face Masks, a Class II surgical mask. The information focuses on non-clinical performance testing against ASTM F2100 standards to demonstrate substantial equivalence to a predicate device.
Here's an analysis of the acceptance criteria and the study that proves the device meets those criteria, based on your requested categories:
1. A table of acceptance criteria and the reported device performance
| Methodology | Purpose | Acceptance Criteria (AQL = 4.0%) | Reported Device Performance (Results) |
|---|---|---|---|
| ASTM F1862 | Determine synthetic blood penetration resistance | 29/32 pass at 160 mmHg | 32/32 Pass per lot at 160 mmHg |
| ASTM F2101 | Determine the bacterial filtration efficiency | ≥ 98% | 32/32 Pass per lot, Average = 99.8% |
| ASTM F2299 | Determine sub-micron particulate filtration efficiency | ≥ 98% | 32/32 Pass per lot, Average = 99.7% |
| MIL-M-36954C or EN 14683 Annex C | Determine breathing resistance or differential pressure | < 6.0 mm H2O/cm² | 32/32 Pass per lot, 3.4 - 4.0 mm H20/cm² |
| 16 CFR Part 1610 | Determine flammability or flame spread | Class 1 | Class 1 |
| ISO 10993-5 (Cytotoxicity) | Biocompatibility | Non-cytotoxic | Non-cytotoxic |
| ISO 10993-10 (Irritation) | Biocompatibility | Non-irritating | Non-irritating |
| ISO 10993-10 (Sensitization) | Biocompatibility | Non-sensitizing | Non-sensitizing |
2. Sample size used for the test set and the data provenance
- Sample Size for performance tests (ASTM F1862, F2101, F2299, MIL-M-36954C/EN 14683): "32/32 Pass per lot" is mentioned for these tests. This implies that 32 samples were tested per lot, and all passed. The document does not specify how many "lots" were tested.
- Sample Size for biocompatibility tests (ISO 10993-5, 10993-10): The sample size for these specific tests is not explicitly stated in the provided text, but the results indicate that the tests were performed "Under the conditions of the study".
- Data Provenance: The document does not specify the country of origin of the data. It is a submission to the U.S. Food & Drug Administration (FDA), suggesting the data was generated for the purpose of meeting U.S. regulatory requirements. The studies are retrospective in the context of the submission, as the tests have already been conducted and the results are being reported.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This section is not applicable to a device like a surgical face mask that relies on objective, standardized physical and material property tests. The "ground truth" for these tests is defined by the ASTM, MIL, EN, and CFR standards themselves, which specify measurable criteria and methodologies. Expert interpretation in the traditional sense (e.g., radiologists reviewing images) is not involved in establishing the "ground truth" for physical performance or biocompatibility.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in studies involving human interpretation or clinical endpoints where there might be disagreement among evaluators of subjective data (e.g., medical image interpretation). For objective physical and material property tests, the outcome is determined by adherence to the standardized test procedure and measurement against defined thresholds.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
This is not applicable. This device is a surgical face mask, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study involving human readers or AI assistance would not be conducted.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is not applicable. This device is not an algorithm or an AI system. It is a physical medical device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The "ground truth" for this device's performance is based on objective, standardized measurements against established criteria defined by international and national standards:
- ASTM F1862: Standard Test Method for Resistance of Medical Face Masks to Penetration by Synthetic Blood.
- ASTM F2101: Standard Test Method for Evaluating the Bacterial Filtration Efficiency (BFE) of Medical Face Mask Materials.
- ASTM F2299: Standard Test Method for Determining the Initial Efficiency of Materials Used in Medical Face Masks to Penetration by Particulates.
- MIL-M-36954C or EN 14683 Annex C: Standards for measuring differential pressure (breathing resistance).
- 16 CFR Part 1610: Standard for the flammability of clothing textiles.
- ISO 10993-5: Biological evaluation of medical devices – Part 5: Tests for in vitro cytotoxicity.
- ISO 10993-10: Biological evaluation of medical devices – Part 10: Tests for irritation and skin sensitization.
The "ground truth" is therefore the metrological result of these tests compared to the numerical thresholds specified in the respective standards.
8. The sample size for the training set
This is not applicable. This document describes the testing of a physical medical device (face mask), not an AI algorithm. Therefore, there is no "training set" in the machine learning sense. The tests are for product verification against established standards.
9. How the ground truth for the training set was established
This is not applicable for the reasons stated in point 8.
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